Levels of depression are higher among Latinos compared to non-Latino whites in the US, and higher for more acculturated Latinos. Depression is higher in Latino women than men. However, despite higher symptoms of depression, Latinos receive fewer mental health services than whites even if they speak English and have insurance. Nurses trained in therapeutic techniques may be effective in community settings where treatment may be more accessible to low income Latina women. The goals of the training aspect of this proposal are to gain knowledge, perform analyses, and engage in evaluation and implementation of the following: a) cultural issues related to mental health interventions with Latino populations; b) cognitive behavioral therapy; c) motivational interviews; and d) culturally appropriate diagnostic interviews for Latinos. The specific aims for research are to describe the feasibility of nurse-led, community-based cognitive behavioral group therapy (CBGT) for 60 low income, second-generation women of Central American and Mexican descent who have major or minor depression or dysthymia. Descriptors of feasibility will include motivators and barriers to therapy (obtained through qualitative methodology) as well as women's stages of readiness to deal with depressive symptoms, measured by the University of Rhode Island Change Assessment (URICA) scale. Lastly, a pilot study will be done to describe the effectiveness of nurse-led CBGT in lowering depression over 8 weeks and to describe the relationship of women's intrinsic strength factors for successful treatment of depression. The intrinsic strength factors will be measured by the modified Wagnild & Young Resilience scale; the modified Pearlin & Schooler Mastery scale; and the modified Burns Life Satisfaction measure. The design is a one-group, quasi-experimental, pre-post, repeated measures study. The analysis includes paired t-tests; one-sample paired, non-parametric Wilcoxon Signed Rank test; one-sample test for proportions; and simple linear regression. Qualitative data on motivations and barriers will be analyzed with Grounded Theory techniques.